197 citations · 326 across the 25 of their papers we have counts for
7 papers · 1 filter
Online Stochastic Variational Gaussian Process Mapping for Large-Scale SLAM in Real Time
Ignacio Torroba, Marco Chella, Aldo Teran +2
Autonomous underwater vehicles (AUVs) are becoming standard tools for underwater exploration and seabed mapping in both scientific and industrial applications \cite{graham2022rapid…
Data-driven Loop Closure Detection in Bathymetric Point Clouds for Underwater SLAM
Jiarui Tan, Ignacio Torroba, Yiping Xie +1
Simultaneous localization and mapping (SLAM) frameworks for autonomous navigation rely on robust data association to identify loop closures for back-end trajectory optimization. In…
Neural Shape-from-Shading for Survey-Scale Self-Consistent Bathymetry from Sidescan
Nils Bore, John Folkesson
Sidescan sonar is a small and cost-effective sensing solution that can be easily mounted on most vessels. Historically, it has been used to produce high-definition images that expe…
Towards Differentiable Rendering for Sidescan Sonar Imagery
Yiping Xie, Nils Bore, John Folkesson
Recent advances in differentiable rendering, which allow calculating the gradients of 2D pixel values with respect to 3D object models, can be applied to estimation of the model pa…
High-Resolution Bathymetric Reconstruction From Sidescan Sonar With Deep Neural Networks
Yiping Xie, Nils Bore, John Folkesson
We propose a novel data-driven approach for high-resolution bathymetric reconstruction from sidescan. Sidescan sonar (SSS) intensities as a function of range do contain some inform…
Neural Network Normal Estimation and Bathymetry Reconstruction from Sidescan Sonar
Yiping Xie, Nils Bore, John Folkesson
Sidescan sonar intensity encodes information about the changes of surface normal of the seabed. However, other factors such as seabed geometry as well as its material composition a…